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Feature Counts vs Salmon quantification

When i am counting through featureCounts after aligning through STAR i am getting around 80091413 reads but when though salmon, i am getting around 45008730.892 reads. Is this acceptable? I am attaching the summary of a particular file when quantified through featureCounts and Salmon

FEATURECOUNTS || Process BAM file CC1_S16_L002_Aligned.sortedByCoord.out.bam...             ||
||    Strand specific : reversely stranded                                    ||
||    Paired-end reads are included.                                          ||
||    The reads are assigned on the single-end mode.                          ||
||    Total alignments : 224209636                                            ||
||    Successfully assigned alignments : 88234705 (39.4%)                     ||
||    Running time : 0.73 minutes
SALMON- expected_format "ISR"
compatible_fragment_ratio   1.0JS:1
num_compatible_fragments    45008731
num_assigned_fragments  45008731
num_frags_with_concordant_consistent_mappings   42512461
num_frags_with_inconsistent_or_orphan_mappings  2570253
strand_mapping_bias 0.000023028011847547505JS:0.000023028011847547503
MSF 0
OSF 0
ISF 979
MSR 0
OSR 0
ISR 42512461
SF  1184869
SR  1384405
MU  0
OU  0
IU  0
U   0

Kindly help me out in this

featurecounts salmon rna-seq star

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1 answer

|| The reads are assigned on the single-end mode. ||

You're counting paired-end data as single-end, hence approximately times 2 of salmon. Count pairs, I think it the flag is something like -P, check manual.

-p and --countReadPairs together for fragments.

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